Showing papers on "Structural health monitoring published in 2007"

An introduction to structural health monitoring

Abstract: This introduction begins with a brief history of SHM technology development. Recent research has begun to recognise that a productive approach to the Structural Health Monitoring (SHM) problem is to regard it as one of statistical pattern recognition (SPR); a paradigm addressing the problem in such a way is described in detail herein as it forms the basis for the organisation of this book. In the process of providing the historical overview and summarising the SPR paradigm, the subsequent chapters in this book are cited in an effort to show how they fit into this overview of SHM. In the conclusions are stated a number of technical challenges that the authors believe must be addressed if SHM is to gain wider acceptance.

Health monitoring of civil infrastructures using wireless sensor networks

Abstract: A Wireless Sensor Network (WSN) for Structural Health Monitoring (SHM) is designed, implemented, deployed and tested on the 4200 ft long main span and the south tower of the Golden Gate Bridge (GGB). Ambient structural vibrations are reliably measured at a low cost and without interfering with the operation of the bridge. Requirements that SHM imposes on WSN are identified and new solutions to meet these requirements are proposed and implemented. In the GGB deployment, 64 nodes are distributed over the main span and the tower, collecting ambient vibrations synchronously at 1 kHz rate, with less than 10 mus jitter, and with an accuracy of 30 muG. The sampled data is collected reliably over a 46-hop network, with a bandwidth of 441 B/s at the 46th hop. The collected data agrees with theoretical models and previous studies of the bridge. The deployment is the largest WSN for SHM.

Review of guided-wave structural health monitoring

Abstract: In this paper we present the state of the art in the field of guided-wave structural health monitoring (SHM). We begin with an overview of damage prognosis, and a description of the basic methodology of guided-wave SHM. We then review developments from the open literature in various aspects of this truly multidisciplinary field. First, we discuss different transducer technologies, including both piezoelectric and non-conventional popular and non-conventional piezoelectric transducers. Next, we examine guided-wave theory, tracing its early history down to modern developments. Following this, we detail the efforts into models for guided-wave excitation by SHM transducers. Then, we review several signal processing related works. The next topic in Section 6 is guided-wave SHM system development, and we explore various packaging ideas, integrated solutions and efforts to examine robustness to different service conditions. We also highlight the broad spectrum of applications in which this technology has been tested. We then present some investigations that have attempted to combine guided-wave approaches with other complementary SHM technologies for better system performance. Finally, we propose desirable developments for further advancement of this field.

Structural Health Monitoring: with Piezoelectric Wafer Active Sensors

Abstract: Structural Health Monitoring (SHM) is the interdisciplinary engineering field devoted to the monitoring and assessment of structural health and durability. SHM technology integrates remote sensing, smart materials, and computer based knowledge systems to allow engineers see how built up structures are performing over time. It is particularly useful for remotely monitoring large infrastructure systems, such as bridges and dams, and high profile mechanical systems such as aircraft, spacecraft, ships, offshore structures and pipelines where performance is critical but onsite monitoring is difficult or even impossible."Structural Health Monitoring with Piezoelectric Wafer Active Sensors" is the first comprehensive textbook to provide background information, theoretical modeling, and experimental examples on the principal technologies involved in SHM. This textbook can be used for both teaching and research. It not only provides students, engineers and other interested technical specialists with the foundational knowledge and necessary tools for understanding modern sensing materials and systems, but also shows them how to employ this knowledge in actual engineering situations.It addresses the problem of aging structures and explains how SHM can alleviate their situation and prolong their useful life. It provides a step by step presentation on how Piezoelectric Wafer Active Sensors (PWAS) are used to detect and quantify the presence of damage in structures. It presents the underlying theories (piezoelectricity, vibration, wave propagation, etc.) and experimental techniques (E/M impedance, PWAS phased arrays, etc.) to be employed in successful SHM applications. It provides an understanding of how to interpret sensor signal patterns such as various wave forms, including analytical techniques like Fast Fourier Transform, Short-time Fourier Transform and Wavelet Transform. It offers comprehensive teaching tools (worked examples, experiments, homework problems, and exercises) and an extensive online instructor manual containing lecture plans and homework solutions.

Effects of environmental and operational variability on structural health monitoring.

Abstract: Stated in its most basic form, the objective of structural health monitoring is to ascertain if damage is present or not based on measured dynamic or static characteristics of a system to be monitored. In reality, structures are subject to changing environmental and operational conditions that affect measured signals, and these ambient variations of the system can often mask subtle changes in the system’s vibration signal caused by damage. Data normalization is a procedure to normalize datasets, so that signal changes caused by operational and environmental variations of the system can be separated from structural changes of interest, such as structural deterioration or degradation. This paper first reviews the effects of environmental and operational variations on real structures as reported in the literature. Then, this paper presents research progresses that have been made in the area of data normalization.

Active health monitoring of an aircraft wing with embedded piezoelectric sensor/actuator network: I. Defect detection, localization and growth monitoring

Abstract: This work focuses on an ultrasonic guided wave structural health monitoring (SHM) system development for aircraft wing inspection. In part I of the study, a detailed description of a real aluminum wing specimen and some preliminary wave propagation tests on the wing panel are presented. Unfortunately, strong attenuation and scattering impede guided waves for large-area inspection. Nevertheless, small, low-cost and light-weight piezoelectric (PZT) discs were bonded to various parts of the aircraft wing, in a form of relatively sparse arrays, for simulated cracks and corrosion monitoring. The PZT discs take turns generating and receiving ultrasonic guided waves. Pair-wise through-transmission waveforms collected at normal conditions served as baselines, and subsequent signals collected at defected conditions such as rivet cracks or corrosion detected the presence of a defect and its location with a novel correlation analysis based technique called RAPID (reconstruction algorithm for probabilistic inspection of defects). The effectiveness of the algorithm was tested with several case studies in a laboratory environment. It showed good performance for defect detection, size estimation and localization in complex aircraft wing structures.

Concrete structural health monitoring using embedded piezoceramic transducers

Abstract: Health monitoring of reinforced concrete bridges and other large-scale civil infrastructures has received considerable attention in recent years However, traditional inspection methods (x-ray, C-scan, etc) are expensive and sometimes ineffective for large-scale structures Piezoceramic transducers have emerged as new tools for the health monitoring of large-scale structures due to their advantages of active sensing, low cost, quick response, availability in different shapes, and simplicity for implementation In this research, piezoceramic transducers are used for damage detection of a 61 m long reinforced concrete bridge bent-cap Piezoceramic transducers are embedded in the concrete structure at pre-determined spatial locations prior to casting This research can be considered as a continuation of an earlier work, where four piezoceramic transducers were embedded in planar locations near one end of the bent-cap This research involves ten piezoceramic patches embedded at spatial locations in four different cross-sections To induce cracks in the bent-cap, the structure is subjected to loads from four hydraulic actuators with capacities of 80 and 100 ton In addition to the piezoceramic sensors, strain gages, LVDTs, and microscopes are used in the experiment to provide reference data During the experiment, one embedded piezoceramic patch is used as an actuator to generate high frequency waves, and the other piezoceramic patches are used as sensors to detect the propagating waves With the increasing number and severity of cracks, the magnitude of the sensor output decreases Wavelet packet analysis is used to analyze the recorded sensor signals A damage index is formed on the basis of the wavelet packet analysis The experimental results show that the proposed methods of using piezoceramic transducers along with the damage index based on wavelet packet analysis are effective in identifying the existence and severity of cracks inside the concrete structure The experimental results demonstrate that the proposed method has the ability to predict the failure of a concrete structure as verified by results from conventional microscopes (MSs) and LVDTs

Damage prognosis: the future of structural health monitoring

Abstract: This paper concludes the theme issue on structural health monitoring (SHM) by discussing the concept of damage prognosis (DP). DP attempts to forecast system performance by assessing the current damage state of the system (i.e. SHM), estimating the future loading environments for that system, and predicting through simulation and past experience the remaining useful life of the system. The successful development of a DP capability will require the further development and integration of many technology areas including both measurement/processing/telemetry hardware and a variety of deterministic and probabilistic predictive modelling capabilities, as well as the ability to quantify the uncertainty in these predictions. The multidisciplinary and challenging nature of the DP problem, its current embryonic state of development, and its tremendous potential for life-safety and economic benefits qualify DP as a ‘grand challenge’ problem for engineers in the twenty-first century.

Strategies for guided-wave structural health monitoring

Abstract: Structural health monitoring (SHM) using guided waves is one of the only ways in which damage anywhere in a structure can be detected using a sparse array of permanently attached sensors. To distinguish damage from structural features, some form of comparison with damage-free reference data is essential, and here subtraction is considered. The detectability of damage is determined by the amplitude of residual signals from structural features remaining after the subtraction of reference data. These are non-zero due to changing environmental conditions such as temperature. In this paper, the amplitude of the residual signals is quantified for different guided-wave SHM strategies. Comparisons are made between two methods of reference signal subtraction and between two candidate sensor configurations. These studies allow estimates to be made of the number of sensors required per unit area to reliably detect a prescribed type of damage. It is shown that the number required is prohibitively high, even in the presence of modest temperature fluctuations, hence some form of temperature compensation is absolutely essential for guided-wave SHM systems to be viable. A potential solution is examined and shown to provide an improvement in signal suppression of approximately 30 dB, which corresponds to two orders of magnitude reduction in the number of sensors required.

Fibre optic methods for structural health monitoring

Abstract: Foreword. Preface. Acknowledgments. 1 Introduction to Structural Health Monitoring. 1.1 Basic Notions, Needs and Benefits. 1.1.1 Introduction. 1.1.2 Basic Notions. 1.1.3 Monitoring Needs and Benefits. 1.1.4 Whole Lifespan Monitoring. 1.2 The Structural Health Monitoring Process. 1.2.1 Core Activities. 1.2.2 Actors. 1.3 On-Site Example of Structural Health Monitoring Project. 2 Fibre-Optic Sensors. 2.1 Introduction to Fibre-Optic Technology. 2.2 Fibre-Optic Sensing Technologies. 2.2.1 SOFO Interferometric Sensors. 2.2.2 Fabry-Perot Interferometric Sensors. 2.2.3 Fibre Bragg-Grating Sensors. 2.2.4 Distributed Brillouin- and Raman-Scattering Sensors. 2.3 Sensor Packaging. 2.4 Distributed Sensing Cables. 2.4.1 Introduction. 2.4.2 Temperature-Sensing Cable. 2.4.3 Strain-Sensing Tape: SMARTape. 2.4.4 Combined Strain- and Temperature-Sensing: SMARTprofile. 2.5 Software and System Integration. 2.6 Conclusions and Summary. 3 Fibre-Optic Deformation Sensors: Applicability and Interpretation of Measurements. 3.1 Strain Components and Strain Time Evolution. 3.1.1 Basic Notions. 3.1.2 Elastic and Plastic Structural Strain. 3.1.3 Thermal Strain. 3.1.4 Creep. 3.1.5 Shrinkage. 3.1.6 Reference Time and Reference Measurement. 3.2 Sensor Gauge Length and Measurement. 3.2.1 Introduction. 3.2.2 Deformation Sensor Measurements. 3.2.3 Global Structural Monitoring: Basic Notions. 3.2.4 Sensor Measurement Dependence on Strain Distribution: Maximal Gauge Length. 3.2.5 Sensor Measurement in Inhomogeneous Materials: Minimal-Gauge Length. 3.2.6 General Principle in the Determination of Sensor Gauge Length. 3.2.7 Distributed Strain Sensor Measurement. 3.3 Interpretation of strain measurement. 3.3.1 Introduction. 3.3.2 Sources of Errors and Detection of Anomalous Structural Condition. 3.3.3 Determination of Strain Components and Stress from Total-Strain Measurement. 3.3.4 Example of Strain Measurement Interpretation. 4 Sensor Topologies: Monitoring Global Parameters. 4.1 Finite Element Structural Health Monitoring Concept: Introduction. 4.2 Simple Topology and Applications. 4.2.1 Basic Notions on Simple Topology. 4.2.2 Enchained Simple Topology. 4.2.3 Example of an Enchained Simple Topology Application. 4.2.4 Scattered Simple Topology. 4.2.5 Example of a Scattered Simple Topology Application. 4.3 Parallel Topology. 4.3.1 Basic Notions on Parallel Topology: Uniaxial Bending. 4.3.2 Basic Notions on Parallel Topology: Biaxial Bending. 4.3.3 Deformed Shape and Displacement Diagram. 4.3.4 Examples of Parallel Topology Application. 4.4 Crossed Topology. 4.4.1 Basic Notions on Crossed Topology: Planar Case. 4.4.2 Basic Notions on Crossed Topology: Spatial Case. 4.4.3 Example of a Crossed Topology Application. 4.5 Triangular Topology. 4.5.1 Basic Notions on Triangular Topology. 4.5.2 Scattered and Spread Triangular Topologies. 4.5.3 Monitoring of Planar Relative Movements Between Two Blocks. 4.5.4 Example of a Triangular Topology Application. 5 Finite Element Structural Health Monitoring Strategies and Application Examples. 5.1 Introduction. 5.2 Monitoring of Pile Foundations. 5.2.1 Monitoring the Pile. 5.2.2 Monitoring a Group of Piles. 5.2.3 Monitoring of Foundation Slab. 5.2.4 On-Site Example of Piles Monitoring. 5.3 Monitoring of Buildings. 5.3.1 Monitoring of Building Structural Members. 5.3.2 Monitoring of Columns. 5.3.3 Monitoring of Cores. 5.3.4 Monitoring of Frames, Slabs and Walls. 5.3.5 Monitoring of a Whole Building. 5.3.6 On-Site Example of Building Monitoring. 5.4 Monitoring of Bridges. 5.4.1 Introduction. 5.4.2 Monitoring of a Simple Beam. 5.4.3 On-Site Example of Monitoring of a Simple Beam. 5.4.4 Monitoring of a Continuous Girder. 5.4.5 On-Site Example of Monitoring of a Continuous Girder. 5.4.6 Monitoring of a Balanced Cantilever Bridge. 5.4.7 On-Site Example of Monitoring of a Balanced Cantilever Girder. 5.4.8 Monitoring of an Arch Bridge. 5.4.9 On-Site Example of Monitoring of an Arch Bridge. 5.4.10 Monitoring of a Cable-Stayed Bridge. 5.4.11 On-Site Example of Monitoring of a Cable-Stayed Bridge. 5.4.12 Monitoring of a Suspended Bridge. 5.4.13 Bridge Integrity Monitoring. 5.4.14 On-Site Example of Bridge Integrity Monitoring. 5.5 Monitoring of Dams. 5.5.1 Introduction. 5.5.2 Monitoring of an Arch Dam. 5.5.3 On-Site Examples on Monitoring of an Arch Dam. 5.5.4 Monitoring of a Gravity Dam. 5.5.5 On-Site Example of Monitoring a Gravity Dam. 5.5.6 Monitoring of a Dyke (Earth or Rockfill Dam). 5.5.7 On-Site Example of Monitoring a Dyke. 5.6 Monitoring of Tunnels. 5.6.1 Introduction. 5.6.2 Monitoring of Convergence. 5.6.3 On-Site Example of Monitoring of Convergence. 5.6.4 Monitoring of Strain and Deformation. 5.6.5 On-Site Example of Monitoring of Deformation. 5.6.6 Monitoring of Other Parameters and Tunnel Integrity Monitoring. 5.7 Monitoring of Heritage Structures. 5.7.1 Introduction. 5.7.2 Monitoring of San Vigilio Church, Gandria, Switzerland. 5.7.3 Monitoring of Royal Villa, Monza, Italy. 5.7.4 Monitoring of Bolshoi Moskvoretskiy Bridge, Moscow, Russia. 5.8 Monitoring of Pipelines. 5.8.1 Introduction. 5.8.2 Pipeline Monitoring. 5.8.3 Pipeline Monitoring Application Examples. 5.8.4 Conclusions. 6 Conclusions and Outlook. 6.1 Conclusions. 6.2 Outlook. References. Index.

A wireless structural health monitoring system with multithreaded sensing devices: design and validation

Abstract: Structural health monitoring (SHM) has become an important research problem which has the potential to monitor and ensure the performance and safety of civil structures. Traditional wire-based SHM systems require significant time and cost for cable installation. With the recent advances in wireless communication technology, wireless SHM systems have emerged as a promising alternative solution for rapid, accurate and low-cost structural monitoring. This paper presents a newly designed integrated wireless monitoring system that supports real-time data acquisition from multiple wireless sensing units. The selected wireless transceiver consumes relatively low power and supports long-distance peer-to-peer communication. In addition to hardware, embedded multithreaded software is also designed as an integral component of the proposed wireless monitoring system. A direct result of the multithreaded software paradigm is a wireless sensing unit capable of simultaneous data collection, data interrogation and wirele...

Development of an impedance-based wireless sensor node for structural health monitoring

Abstract: This paper presents the development and application of a miniaturized impedance sensor node for structural health monitoring (SHM). A large amount of research has been focused on utilizing the impedance method for structural health monitoring. The vast majority of this research, however, has required the use of expensive and bulky impedance analyzers that are not suitable for field deployment. In this study, we developed a wireless impedance sensor node equipped with a low-cost integrated circuit chip that can measure and record the electrical impedance of a piezoelectric transducer, a microcontroller that performs local computing and a wireless telemetry module that transmits the structural information to a base station. The performance of this miniaturized and portable device has been compared to results obtained with a conventional impedance analyzer and its effectiveness has been demonstrated in an experiment to detect loss of preload in a bolted joint. Furthermore, for the first time, we also consider the problem of wireless powering of such SHM sensor nodes, where we use radio-frequency wireless energy transmission to deliver electrical energy to power the sensor node. In this way, the sensor node does not have to rely on an on-board power source, and the required energy can be wirelessly delivered as needed by human or a remotely controlled robotic device.

Structural health monitoring using piezoelectric impedance measurements.

Abstract: This paper presents an overview and recent advances in impedance-based structural health monitoring. The basic principle behind this technique is to apply high-frequency structural excitations (typically greater than 30 kHz) through surface-bonded piezoelectric transducers, and measure the impedance of structures by monitoring the current and voltage applied to the piezoelectric transducers. Changes in impedance indicate changes in the structure, which in turn can indicate that damage has occurred. An experimental study is presented to demonstrate how this technique can be used to detect structural damage in real time. Signal processing methods that address damage classifications and data compression issues associated with the use of the impedance methods are also summarized. Finally, a modified frequency-domain autoregressive model with exogenous inputs (ARX) is described. The frequency-domain ARX model, constructed by measured impedance data, is used to diagnose structural damage with levels of statistical confidence.

Practical implementation of optical fiber sensors in civil structural health monitoring

Abstract: Implementation of successful civil structural health monitoring strategies requires selection and placement of sensors suitable for measurement of key parameters that influence the performance and health of the structural system. Optical fiber sensors have been successfully implemented in aeronautics, mechanical systems, and medical applications. Civil structures pose further challenges in monitoring mainly due to their large dimensions, diversity as well as heterogeneity of materials involved, and hostile construction environment. This article provides a summary of basic principles pertaining to practical health monitoring of civil engineering structures with optical fiber sensors. The issues discussed include basic sensor principles, strain transfer mechanism, sensor packaging, sensor placement in construction environment, and reliability and survivability of the sensors.

Issues in structural health monitoring employing smart sensors

Abstract: Smart sensors densely distributed over structures can provide rich information for structural monitoring using their onboard wireless communication and computational capabilities However, issues such as time synchronization error, data loss, and dealing with large amounts of harvested data have limited the implementation of full-fledged systems Limited network resources (eg battery power, storage space, bandwidth, etc) make these issues quite challenging This paper first investigates the effects of time synchronization error and data loss, aiming to clarify requirements on synchronization accuracy and communication reliability in SHM applications Coordinated computing is then examined as a way to manage large amounts of data

Synchronized switch harvesting applied to self-powered smart systems: Piezoactive microgenerators for autonomous wireless receivers

Abstract: This paper introduces the conceptual architecture of a fully integrated, truly self-powered structural health monitoring (SHM) scheme. The challenge here is to power an array of numerous distributed actuators and sensors as well as wireless data transmission modules without recurring to heavy and costly wiring. Based on microgenerators which directly convert ambient mechanical energy into electrical energy, using the synchronized switch harvesting (SSH) method, the proposed solution allows avoiding the periodic replacement or reloading of batteries. This addresses environmental and economic issues at the same time, knowing that such elements are heavy, polluting and might be installed in rather inaccessible locations. Indeed, especially in airborne structures saving weight and maintenance cost is of priority importance. Previous work showed that such microgenerators provide a stand-alone power source, whose performances meet the requirements of autonomous wireless transmitters (AWTs) that comprise an acoustic Lamb wave's actuator and a radio frequency (RF) emitter (D. Guyomar, Y. Jayet, L. Petit, E. Lefeuvre, T. Monnier, C. Richard, M. Lallart, Synchronized switch harvesting applied to self-powered smart systems: Piezoactive microgenerators for autonomous wireless transmitters, Sens Actuators A: Phys. 138 (1) (2007) 151–160, doi:10.1016/j.sna.2007.04.009 ). Following this work, the present contribution presents a further step towards the integration of the SHM technique. It shows the ability of our microgenerators to provide enough energy to give logical autonomy to each self-powered sensing node, named autonomous wireless receiver (AWR), and thus to provide some local (decentralized) pre-processing ability to the SHM system. A preliminary design of the device using off-the-shelf electronics and surface mounted piezoelectric patches will be presented. Since the existence of a positive energy balance between the harvesting capabilities of the SSH technique and the energy requirements of the proposed device will be proved, the system formed by the combination of the AWR with the previously developed AWT, is a proof of concept of truly self-powered smart systems for damage detection in simple structures, setting apart application-specific optimization or miniaturization concerns that will be addressed in future works.

Development of Distributed Long-gage Fiber Optic Sensing System for Structural Health Monitoring

Abstract: The essence of structural health monitoring (SHM) requires an innovative sensing system similar to a human nervous system throughout the whole body to catch comprehensive information without losing structural integrity. In a recent research by the authors, an integrated structural assessment strategy based on distributed strain sensing technologies is proposed [1], which has been dedicated to utilize the strain distribution throughout the full or some partial areas of structures to detect the arbitrary and unforeseen damage. To implement such strategy, a typical distributed fiber optic sensing system is developed by extending the gage length of fiber Bragg grating (FBG) and then arranging the long-gage FBG sensors in series. This article summarizes the packaging design and manufacture method of such long-gage FBG sensors and verifies the performance of the developed sensors and the distributed sensing system by using a series connection of long-gage FBG sensors. Combined with the practical application in ...

Guided-wave signal processing using chirplet matching pursuits and mode correlation for structural health monitoring

Abstract: Signal processing algorithms for guided wave pulse echo-based structural health monitoring (SHM) must be capable of isolating individual reflections from defects in the structure, if any, which could be overlapping and multimodal. In addition, they should be able to estimate the time–frequency centers, the modes and individual energies of the reflections, which would be used to locate and characterize defects. Finally, they should be computationally efficient and amenable to automated processing. This work addresses these issues with a new algorithm employing chirplet matching pursuits followed by a mode correlation check for single point sensors. Its theoretical advantages over conventional time–frequency representations for SHM are elaborated. Results from numerical simulations and experiments in isotropic plate structures are presented, which show the capability of the proposed algorithm. Finally, the issue of in-plane triangulation is discussed and experimental work done to explore this issue is presented.

Active health monitoring of an aircraft wing with an embedded piezoelectric sensor/actuator network: II. Wireless approaches

Abstract: The objective of this study is to develop a wireless ultrasonic structural health monitoring (SHM) system for aircraft wing inspection. In part I of the study (Zhao et al 2007 Smart?Mater.?Struct. 16 1208?17), small, low cost and light weight piezoelectric (PZT) disc transducers were bonded to various parts of an aircraft wing for detection, localization and growth monitoring of defects. In this part, two approaches for wirelessly interrogating the sensor/actuator network were developed and tested. The first one utilizes a pair of reactive coupling monopoles to deliver 350?kHz RF tone-burst interrogation pulses directly to the PZT transducers for generating ultrasonic guided waves and to receive the response signals from the PZTs. It couples enough energy to and from the PZT transducers for the wing panel inspection, but the signal is quite noisy and the monopoles need to be in close proximity to each other for efficient coupling. In the second approach, a small local diagnostic device was developed that can be embedded into the wing and transmit the digital signals FM-modulated on a 915?MHz carrier. The device has an ultrasonic pulser that can generate 350?kHz, 70?V tone-burst signals, a multiplexed A/D board with a programmable gain amplifier for multi-channel data acquisition, a microprocessor for circuit control and data processing, and a wireless module for data transmission. Power to the electronics is delivered wirelessly at X-band with an antenna?rectifier (rectenna) array conformed to the aircraft body, eliminating the need for batteries and their replacement. It can effectively deliver at least 100?mW of DC power continuously from a transmitter at a range of 1?m. The wireless system was tested with the PZT sensor array on the wing panel and compared well with the wire connection case.

Design of a structural health monitoring system for long-span bridges

Abstract: Structural health monitoring systems (SHMSs) have been adopted over the past decade to monitor and evaluate the structural health condition of long-span bridges. A SHMS is currently included as a standard mechatronic system in the design and construction of most large-scale and multi-disciplinary bridge projects, such as Stonecutters Bridge and SuTong Bridge in Hong Kong and China. The modular concept used in the design of the SHMSs for Tsing Ma Bridge, Kap Shui Mun Bridge and Ting Kau Bridge has a significant influence on the design of new SHMSs in Hong Kong and China. This modular concept has, however, been enhanced in the detailed design of the SHMS for Stonecutters Bridge by the Highways Department of Hong Kong. This paper introduces the enhanced modular concept of six integrated modules in terms of their respective functional performance requirements. The six integrated modules are the sensory system, the data acquisition and transmission system, the data processing and control system, the structural...

An Investigation Into the Temperature Stability of a Guided Wave Structural Health Monitoring System Using Permanently Attached Sensors

Abstract: When testing complex structures using a deployable guided wave system, the measured signals are often far too complex to directly interpret without a priori knowledge of the geometry of the structure. However, in a structural health monitoring (SHM) scenario, the sensors are permanently attached to the structure and so changes in the system can be monitored by comparison to an earlier baseline measurement, taken when the structure was undamaged. This paper investigates such a system for the SHM of plate-like structures using guided waves. The basis of the system is a distributed array of permanently attached piezoelectric guided wave transducers where pairs of transducers are used in pitch-catch configuration allowing the detection and localization of damage in the plate. It has been observed that the use of a single baseline measurement suffers in the medium to long-term due to the variation of environmental conditions. A key parameter in the instability is the change in the temperature of the test structure. A method of using a database of baselines, termed optimal baseline subtraction (OBS), is described and applied to an experimental SHM system. The objective of this paper is to investigate the suitability and robustness of OBS under varying rates of temperature change and its use in the localization of damage. Results have shown that through the OBS an improvement of up to 20 dB in signal-to-coherent noise ratio may be achieved compared with single baseline subtraction

Time-frequency and time-scale analyses for structural health monitoring

Abstract: Signal processing is one of the most important elements of structural health monitoring. This paper documents applications of time-variant analysis for damage detection. Two main approaches, the time–frequency and the time–scale analyses are discussed. The discussion is illustrated by application examples relevant to damage detection.

Built-in sensor network for structural health monitoring of composite structure

Abstract: By implementing a built-in sensor network on a composite structure, crucial information regarding the condition, damage state, and service environment of the structure can be obtained. In this study, methods for integrating piezoelectric sensor networks into a composite structure during different fabrication processes, including the resin transfer molding (RTM) and filament winding processes, are examined. To integrate sensor networks with different contours of structures, the method to fabricate a three-dimensional (3-D) diagnostic layer is developed. It is demonstrated that a large number of sensors supported on a thin flexible dielectric film, called a SMART Layer, offers a simple and efficient way to integrate a large sensor network onto a complex 3-D structure. The sensor network permanently embedded inside the composite structures can be used with either active sensing or passive sensing to monitor the health condition of a structure throughout its lifetime.

Limitations in Structural Identification of Large Constructed Structures

Abstract: The objective of this paper is to discuss the limitations in structural identification of large constructed structures. These limitations arise due to the geometric complexity, uncertain boundary and continuity conditions, loading environment, and the imperfect knowledge and errors in modeling such large constructed facilities. In this paper, the writers present their studies on developing a mixed microscopic-structural element level three-dimensional finite-element (FE) modeling of a long-span bridge structure and its structural system identification by integrating various experimental techniques. It is shown that a reasonable level of confidence (50–90%) can be achieved with a model that is calibrated using global and local structural monitoring data with a sufficiently high spatial resolution. The reliability of the global attributes, such as boundary and continuity conditions that may be identified and simulated by means of field-calibrated models using only dynamic test results (globally calibrated m...

Least-Squares Estimation with Unknown Excitations for Damage Identification of Structures

Abstract: System identification and damage detection for structural health monitoring of civil infrastructures have received considerable attention recently. Time domain analysis methodologies based on measured vibration data, such as the least-squares estimation and the extended Kalman filter, have been studied and shown to be useful. The traditional least-squares estimation method requires that all the external excitation data (input data) be available, which may not be the case for many structures. In this paper, a recursive least-squares estimation with unknown inputs (RLSE-UI) approach is proposed to identify the structural parameters, such as the stiffness, damping, and other nonlinear parameters, as well as the unmeasured excitations. Analytical recursive solutions for the proposed RLSE-UI are derived and presented. This analytical recursive solution for RLSE-UI is not available in the previous literature. An adaptive tracking technique recently developed is also implemented in the proposed approach to track the variations of structural parameters due to damages. Simulation results demonstrate that the proposed approach is capable of identifying the structural parameters, their variations due to damages, and unknown excitations.